In today's data centers, the clusters of servers in a client-server network that run business applications often do a poor job of managing unpredictable workloads. One server may sit idle, while another is constrained. This leads to a “Catch-22” where companies, needing to avoid network bottlenecks and safeguard connectivity with customers, business partners and employees, often plan for the highest spikes in workload demand, then watch as those surplus servers operate well under capacity most of the time.
In grid computing, all of the disparate computers and systems in an organization or among organizations become one large, integrated computing system. That single integrated system can then handle problems and processes too large and intensive for any single computer to easily handle in an efficient manner.
More specifically, grid computing is a form of distributed system wherein computing resources are shared across networks. Grid computing enables the selection, aggregation, and sharing of information resources resident in multiple administrative domains and across geographic areas. These information resources are shared, for example, based upon their availability, capability, and cost, as well as a user's quality of service (QoS) requirements. Grid computing can mean reduced cost of ownership, aggregated and improved efficiency of computing, data, and storage resources, and enablement of virtual organizations for applications and data sharing.